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Leverage the voice of your customers.


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Leverage the voice of your customers.

  1. 1. Leverage the voice of your customers. An Anderson Analytics and SPSS predictive text analytics case study. In the new information age, any customer can become a brand enemy or evangelist and reach millions of other customers on the web. These opinions, expressed freely on the internet, encompass attitudes, thoughts and behaviors of past, current and potential customers.
  2. 2. Companies are rushing to tap into the explosion of customer opinions expressed online. The most innovative companies know they could be even more successful in meeting customer needs, if they just understood them better. Text analytics is proving to be an invaluable tool in doing this. Anderson Analytics, a full-service market research consultancy, tackles this issue using cutting-edge text analytics and data mining software from SPSS that allows the application of linguistic, statistical and pattern recognition techniques to extremely large text data sets. A text analytics project is usually part of a much larger data mining project that would typically involve the identification of some core strategic questions, the allocation of resources and the eventual implementation of findings. However, the focus of this case study is to describe the tactical aspects of a text analytics project and to delineate the three basic steps involved in text analytics: • Data Collection and Preparation • Text Coding and Categorization • Text Mining and Visualization In this case study, Anderson Analytics “content-mined” data available on’s discussion boards. is one of the most highly trafficked travel domains. It features chat boards and discussions that cover the most up-to-date traveler information, as well as loyalty programs for both airlines and hotels. Note that the text analytics techniques applied in this case are not limited to discussion boards or blogs but can be applied to any text data source, including survey open ends, call center logs, customer complaint/suggestion databases, emails, etc.
  3. 3. Step 1: Data Collection & Preparation discussion topics, topic ID, topic starter, and topic start H aving quality data in the proper format is usually more than half of the battle for most researchers. For those who can gain direct access to a well-maintained cutomer date. Then, by using the topic ID, the web-scraping application constructs and submits query strings to the database, the data collection and preparation process is site to retrieve messages associated with relatively painless. However, for researchers who want to each specific topic. study text information that exists in a public forum such as A good web-scraping tool should allow the capture of, data collection can be more complex and information that exists in the source data of an html page, usually involves web-scraping. not just the displayed text. Therefore, hidden information Web scraping (or screen such as the topic ID, date stamp, etc. also becomes “It is crucial for us to get an scraping) is a technique used available to the researcher. understanding of how our to extract data from websites Besides making sure the fields in the final dataset are in that display output generated most loyal customers think the correct format, another problem unique to discussion from another program. There board text needs to be addressed. It is very common for and what they value most are many commercially posters to quote others’ text within their own posts. These in their travel experience… available applications that quotes should typically be extracted from the message field can scrape a website and turn any data that helps us and placed in a separate field so as to prevent double the blogs or forum messages counting and inadvertently weighting certain posts. meet our loyal customers into a data table. and attend to needs of In addition to the text messages posted on the forum, the Even with the availability of web-scraping process should also capture the poster’s future customers is worth powerful web-scraping tools ID and ‘handle’ as well as any other available poster and techniques, text mining its weight in gold.” a popular blog or a message information such as forum join date and forum registration information (in this case: location, frequent traveler board like the one at Robin Korman, presents program affiliation, etc.) Vice President, Starwood unique data collection and Loyalty Marketing Program processing challenges. WEB SCRAPING PROCESS The amount of free text CRAWL available on such sites usually Crawl the website and scrape prohibits an indiscriminate approach to data scraping. for topic, ID and thread initiator. A strategy with clear objectives and a well-defined data extraction method are needed in order to increase the reli- DOWNLOAD ability of data analysis in the latter stages of the research. Use topic ID from the first step as part of the URL query string In this particular case, researchers at Anderson Analytics to download messages. narrowed the scope to just discussion topics within a 12-month period (from August 2005 to August 2006) STORE on the five major forums intended for discussing the Web crawl and store message display pages. hotel loyalty programs of Starwood, Hilton, Marriott, Inter SCREEN SCRAPE Continental, and Hyatt hotels. Screen scrape stored webpages and extract data Specific web-scraping parameters differ depending on the into a structured format. structure of the target sites. In a discussion board format, LINK the text data tend to follow a simple hierarchy. Typically, Link extracted posts with topics from the first each forum contains a list of topics, and each topic step, along with other extracted fields to create consists of numerous posts. Therefore, the web-scraping the final dataset. process of initially retrieves data such as the
  4. 4. Step 2: Text Coding & Categorization T ext coding and categorization is the process of assign- ing each text data record a numeric value that can be used later for statistical analysis. CODING & CATEGORIZATION PRELIMINARY CODING Text coding can apply either dichotomous codes (flags & Use both computer and human coder to obtain many variables) or categorical codes (one variable for an the preliminary understanding of the data. entire dataset). Short answers to an open-ended survey question typically use categorical codes. However, the INITIAL CLASSIFICATION amount of text included in most discussion board posts Use SPSS Text Mining tool to perfrom initial typically requires dichotomous codes. categorization on a sample data set (1/100 of the entire dataset). Text coding is usually an iterative process. This is particularly true for coding messages on a site such as COMPUTER CLASSIFICATION This is because compared to survey Information and knowledge gained from the answers, the text information from discussion boards tends initial concept extraction is used by human coder to be less focused. The text data on most discussion boards to assist in computer categorization. tend to be “user-driven” rather than “provider-driven.” CODING & CLASSIFICATION REFINEMENT Before creating categories, researchers at Anderson Categorization and coding are an iterative Analytics first randomly examine a sample of text messages process. Custom libraries are created to refine to gain a basic understanding of the data. This step is the process. Text extraction is performed required to understand the type of acronyms, shorthand multiple times until the number of and the and terminologies commonly used on the forum of interest. details of categories are satisfactory. SPSS Text Analysis for CODING & EXTRACTION RULES Surveys and Text Mining Once the coding result becomes satisfactory, for Clementine are powerful the same coding and extraction rules are used “I strongly believe that the tools. However, the text on the entire dataset. travel industry can not coding results can be CATEGORIZATION RESULTS greatly improved if the Categorization results are exported for further only learn by listening programs can be “trained” analysis with tools such as SPSS Text Analysis. to their customers in to better understand real-time, but that by text information particular to the industry and topics being active where the of interest. customers are on the With a list of industry Internet, they can create specific themes, concepts a unique generation of and words, the researchers at Anderson use tools such loyal, repeat customers… as SPSS Text Analysis for Customer service Surveys to create a custom these days is where dictionary. Then the SPSS text analytics applications the customer is, not can be used, in conjunction In this case, examples of some of the basic concepts where you are” with an SPSS developed in the messages that can be detected by the software dictionary, to extract highly include: ‘rates’, ‘stay’, ‘breakfast’, ‘points’, ‘free offers’. The Randy Petersen, relevant concepts from text extraction and categorization processes are repeated CEO the text data. with minor modification each time to fine tune results.
  5. 5. Step 3: Text Mining & Visualization T he coded text data can be interpreted in many different ways depending on the needs of any given research project. In this case, the data is examined “Understanding the needs of your customers as well as the strengths and weaknesses of your via the following methods: competitors is paramount for building brands Positive/Negative comments and overlapping terms that people love. Thus, I believe that the mining The data indicate that negative discussions of customer comments on the web will become among the posters are centered on the payment process, a cornerstone for future innovation and the condition/quality of the bathroom, furniture, and the check in/out process. The praises seem to be centered around detection of competitive threats.” topics such as spa facility, complimentary breakfasts, points and promotions. Isaac Collazo, Vice President, Performance Strategy & Planning Data patterns within different hotel brands InterContinental Hotels Group By comparing the coded text data of Starwood and Hilton forums, the researchers find that the posters seem to be rela- tively more pleased with beds on Starwood’s board, but more pleased with food and health club facilities on Hilton’s board. Longitudinal data patterns CONCLUSION As this study contains data from a one year period, data Companies have found that they can compete far can be analyzed to understand how topics are being more effectively if they gain a true, 360º view of their discussed on a month-to-month basis. The data in this customers. The feedback that current and potential particular case revealed that the discussion about “promo- customers provide in blogs, forums and other online tions” on the Starwood board was particularly frequent spaces provides a rich source of feedback. Using in February 2006. Cross-checking with Starwood manage- text analytics to monitor this information helps ment confirmed that special promotions were launched organizations gauge customer reaction to products during that time period. This demonstrates one way to and services and, when combined with analysis of measure the impact of various communication strategies, “structured” transactional data, delivers predictive promotions and even non-planned external events. insight into customer behavior. Analysis of Poster Groups This paper described how text analytics was applied to Web mining may be helpful in understanding the aggregate information posted by users of travel and hospitality motivation of some of the most active users of the products. services; but the same techniques can be applied to Though it may be difficult to segment posters with only other industries. A company might find, for example, one post, frequent posters can provide a relatively rich that when it launches a special promotion, customers set of segmentation variables. In this case, some general mention the offer frequently in their online posts. motivational themes found were the need for being ‘in the Text analytics can help identify this increase, as well know’, ‘finding deals’, and the desire to “give back”. as the ratio of positive/negative posts relating to the promotion. It can be a powerful validation tool to ANALYSIS complement other primary and secondary customer Super Posters – research and feedback management initiatives. Connectors vs. Loyalists. Companies that improve their ability to navigate and Analysis using text mine the boards and blogs relevant to their Clementine’s Web industry are likely to gain a considerable information Visualization Tool advantage over their competitors.
  6. 6. Find out how you too can harness the power of text analytics. Contact Anderson Analytics & SPSS. About Anderson Analytics More than Market Research, Anderson Analytics is a next generation marketing consultancy that combines new technologies, such as data and text mining, with traditional market research. We focus on helping clients Gain the Information Advantage by combining the efficiencies and business experience found in large research firms with the rigorous methodological understanding from academia and the creativity found only in smaller firms. Our clients put their customers first and so do we, visit our website to learn about “The AA-Assurance.” About SPSS Inc: SPSS Inc. (Nasdaq: SPSS) is a leading global provider of predictive analytics software and solutions. The company’s predictive analytics technology improves business processes by giving organizations forward visibility for decisions made every day. By incorporating predictive analytics into their daily operations, organizations become Predictive Enterprises— able to direct and automate decisions to meet business goals and achieve a measurable competitive advantage. More than 250,000 public sector, academic, and commercial customers rely on SPSS technology to help increase revenue, reduce costs, and detect and prevent fraud. Founded in 1968, SPSS is headquartered in Chicago, Illinois. SPSS TEXT ANALYSIS FOR SURVEYS™ SPSS Text Analysis for Surveys uses natural language processing (NLP) software technologies and allows users to combine automated and manual techniques in analyzing open-ended responses to survey questions. SPSS Text Analysis for Surveys is uniquely able to distinguish between positive and negative comments and opinions, which is extremely valuable in understanding customer feedback. TEXT-MINING FOR CLEMENTINE® Text Mining for Clementine enables users to extract key concepts, sentiments and relationships from textual or “unstruc- tured” data and convert them to a structured format that can be used to create predictive models. This has been shown to improve the “lift” or accuracy of predictive data models and significantly improve results. About Founded in 1986, Frequent Flyer Services has created a unique niche for itself within the travel industry as a company that conceives, develops and markets products and services exclusively for the frequent traveler. Its focus and distinctive competency lie in the area of frequent traveler programs. Worldwide, these frequent traveler programs in the airline, hotel, car rental and credit card industries have more than 75 million members who earn an excess of 650 billion miles per year. Headed by Randy Petersen, who The Wall Street Journal calls, “...the most influential frequent flier in America,” Frequent Flyer Services has had alliances with major companies such as AOL and provides, or has provided, content and information to many of the leading sites on the Internet. The company is probably most famous for its Inside Flyer magazine, which has grown from a simple newsletter into the leading publication in the world for members of frequent traveler programs. Anderson Analytics, LLC SPSS Inc. 154 Cold Spring Road, Suite 80 233 S. Wacker Drive, 11th Floor Stamford, CT 06905 Chicago, IL 60606 Tel: +1.888.891.3115 Tel: +1.312.651.3000